Price differentiation under narrow MFNs ACE annual conference 2017 Tim Reuter 17 November 2017

Introduction Various national competition authorities investigated online travel agents’ (OTAs) most favoured nation clauses; RBB advised Booking.com during these investigations Two flavours of MFNs Wide MFN / horizontal parity: Hotels cannot post lower prices on competing OTAs than on Booking.com vs Narrow MFN / vertical parity: Hotels cannot post lower prices on own websites than on Booking.com Prevention of free-riding as a potential efficiency rationale (not discussed today) Relevance also in the broader context of the CMA’s and BKartA’s investigation into digital comparison websites (and the CMA’s resulting case for home insurance comparison websites) 17 November 2017

Overview Introduction Theory of harm A timeline of events Testable hypotheses of the theory of harm Analysis of price differentiation Description of the data set Analysis and results Shortcomings of data set 17 November 2017

Theory of harm Wide MFN If OTAs cannot obtain lower room rates than Booking.com, OTAs have no incentive to lower commission rates in exchange for lower room rates => Competition between OTAs harmed (and between hotels) Narrow MFN A lower price on some OTA than on Booking.com implies that the price on this OTA is below the price on the hotel’s website => Hotels risk cannibalizing direct sales If cost of generating a direct booking is below OTA commission rates, hotels would be unwilling to set higher prices on their own websites than on OTAs => Narrow MFNs may replicate the effects of wide MFNs 17 November 2017

A timeline of events Analyses presented were conducted between May and November 2016 Aug 2015: French parliament adopts legislation blocking narrow MFNs. However, by obtaining preferred status with Booking.com, hotels opt-in to accepting narrow MFNs again Dec 2013: BKA prohibits HRS’ (wide) MFNs – confirmed in appeal Forthcoming: Higher Regional Court Düsseldorf to decide on Booking.com’s appeal Dec 2015: BKA prohibits Booking.com’s narrow MFNs Feb / Apr 2017: ADLC and ECN issue review of switch from wide to narrow MFNs Jul 2015: Narrow MFNs accepted as commitments by a number of CAs 17 November 2017

Testable hypotheses of the theory of harm Hotel pricing data allow to test the theory of harm Assumption that hotels are unwilling to set higher prices on their own website than on OTAs Are there instances of higher prices on hotel websites than on OTAs? Prediction that there is little price differentiation under narrow MFNs Is there price differentiation between OTAs? Prediction that price differentiation between OTAs under narrow MFNs is lower than under no MFNs Test by comparing price differentiation under different MFN policies Before-and-after the prohibition decision in Germany Between preferred and standard accommodations in France Diff-and-diff under benchmarking these comparison to those in other countries 17 November 2017

2. Analysis of price differentiation 17 November 2017

Description of the data set Both OTAs and (sometimes) hotels post prices on metasearch-sites (MSS) such as Trivago and TripAdvisor Internet bot queries MSSs for a set of selected hotels and records prices founds on OTAs and the hotels’ websites Mimics consumer behaviour Records for each OTA (and direct distribution) the cheapest price of a given hotel Operates as part of Booking.com’s ordinary course of business Representative sample for all accommodations found on Booking.com (only about 15% of accommodations; but representing > 80% of revenues) We assessed data for 12 ECN working group countries (plus Austria and Switzerland) Only available after Booking.com implemented commitments (i.e. no comparison of wide to narrow MFNs possible) 17 November 2017

MSS Screenshot 17 November 2017

Practical problems assessing the data Large data set Close to 50,000 hotels queried (in relevant countries); each queried six times per day -> 54 million queries Each query can return up to one price per OTA, corresponding to one observation Raw data set with several hundred million observations and >100GB size Limited access to the raw data by advisors Client was running SQL scripts providing aggregated data for our specific needs, e.g. number of searches, in which price on Booking.com ≠ price on other OTAs Limited number of analyses we could run Limited visibility on some data specificities (e.g. changes in the booking window and length of stay adopted) 17 November 2017

Result 1: Evidence of higher prices on hotel websites Share of searches for which prices in direct distribution are above the prices of at least one OTA Prices in direct distribution higher than on OTAs in a significant share of searches Figures contradict the centrepiece assumption of the theory of harm Similar figures are robustly found across all countries and subsamples of accommodations Average share of searches for which price in direct distribution is higher than on OTAs Proportion of hotels that are cheaper on OTAs on more than 50% of searches [10-15%] [5-10%] 17 November 2017

Result 2: Price differentiation under narrow MFNs Definition out-of-parity-rate (OOP): share of searches with price on at least one OTA ≠ price on Booking.com Significant level of price differentiation between OTAs under narrow MFNs Hotels can set different prices on different OTAs (in exchange for lower commission rate) Result robust for all countries and hotels subject to narrow MFNs Is the level of price differentiation lower than it would be under no MFNs? Average OOP-rate Proportion of hotels with OOP-rate of at least 50% [35-40%] 17 November 2017

Result 3: Price differentiation under no MFNs not higher than under narrow MFNs Comparison between preferred and standard accommodations in France benchmarked on other countries (OOPFrance_Preferred – OOPFrance_Standard) – (OOPECN_Preferred – OOPECN_Standard)>0 No evidence that hotels not subject to narrow MFNs price differentiate more than others Confirmed by regression analysis relying on both German and France “experiment”  OOP-rate France Rest of ECN WG Delta Standard [35-40%] [2-4pp] Preferred [40-45%] [0-2pp] [8-10pp] [6-8pp]   17 November 2017